Derivative-Free and Blackbox Optimization

di Charles Audet (Autore)

Warren Hare (Autore)

Springer Nature Switzerland AG, 2026

The second edition of Derivative-Free and Blackbox Optimization offers a comprehensive introduction to the field of optimization when derivatives are unavailable, unreliable, or impractical. Whether you’re a student, instructor, or self-learner, this book is designed to guide you through both the foundations and advanced techniques of derivative-free and blackbox optimization. This new edition features significantly expanded exercises, updated and intuitive notation, over 30 new figures, and a wide range of pedagogical enhancements aimed at making complex concepts accessible and engaging. The book is structured into five parts. Part 1 established foundational principles, including an expanded chapter on proper benchmarking. Parts 2, 3, and 4, take an in-depth look at heuristics, direct search, and model based approaches (respectively). Part 5 extends these approaches to specialised settings. Finally, a new appendix contributed by Sébastien Le Digabel, details several real-world applications of blackbox optimization, and links to software for each application. Whether used in the classroom or for independent exploration, this book is a powerful resource for understanding and applying optimization methods – no gradients required. 

• Autore: Charles Audet, Warren Hare
• Editore: Springer Nature Switzerland AG
• Collana: Springer Series in Operations Research and Financial Engineering
• Anno: 2026
• Rilegatura: Hardback
• Pagine: 425 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783032009050

Testo in English